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-cs229-numpy- icon -cs229-numpy-

numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法

ailearning icon ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

bert icon bert

TensorFlow code and pre-trained models for BERT

bert-bilstm-crf-ner icon bert-bilstm-crf-ner

Tensorflow solution of NER task Using BiLSTM-CRF model with Google BERT Fine-tuning And private Server services

bilm-tf icon bilm-tf

Tensorflow implementation of contextualized word representations from bi-directional language models

char-rnn-tensorflow icon char-rnn-tensorflow

Multi-layer Recurrent Neural Networks (LSTM, RNN) for character-level language models in Python using Tensorflow

chinese-clip icon chinese-clip

Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.

chinese-poetry icon chinese-poetry

The most comprehensive database of Chinese poetry 🧶最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人,21050首词。

chinesener icon chinesener

中文命名实体识别,实体抽取,tensorflow,pytorch,BiLSTM+CRF

cornucopia-llama-fin-chinese icon cornucopia-llama-fin-chinese

聚宝盆(Cornucopia): 中文金融系列开源可商用大模型,并提供一套高效的金融垂直领域LLM训练框架(Pretraining、SFT、RLHF、Quantize等)

crf icon crf

Simple implementation of Conditional Random Fields (CRF) in Python. A faster, more powerful, Cython implementation is available in the vocrf project https://github.com/timvieira/vocrf

crf-1 icon crf-1

A pure-Python implementation of the Linear-Chain Conditional Random Fields

datasets icon datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

deebert icon deebert

DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference

dive-into-dl-tensorflow2.0 icon dive-into-dl-tensorflow2.0

本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的认可

eda_nlp icon eda_nlp

Data augmentation for NLP, presented at EMNLP 2019

eda_nlp_for_chinese icon eda_nlp_for_chinese

An implement of the paper of EDA for Chinese corpus.中文语料的EDA数据增强工具。NLP数据增强。论文阅读笔记。

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